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A method for detecting suspicious regions in mammograms based on multiscale image filtering and regression-line analysis

机译:基于多尺度图像滤波和回归线分析检测乳房X线图中可疑区域的方法

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Early detection of breast cancer is an important task for preventing the loss of lives/breasts of the women. In this paper we propose a method for detecting suspicious features of breast cancers on mammograms by the combination of multiscale image filtering and regression-line analysis. Images are represented and analyzed at different scales. Calcifications are detected on the finest resolution, masses and mammary glands are detected on a more abstracted plane. After detecting mammary glands, we apply linear regression to the parts of mammary ducts, and estimates the degree of concentration by the measure of average minimal distance to the concentration point. Experimental results on the DDSM mammography images demonstrate that these approaches could contribute to the successful detection of these features.
机译:乳腺癌的早期发现是防止妇女生命/乳房丧失的重要任务。在本文中,我们提出了一种通过多尺度图像滤波和回归线分析的组合来检测乳腺癌的可疑特征。以不同的尺度表示和分析图像。在最佳分辨率上检测到钙化,在更抽象的平面上检测到质量和乳腺。在检测乳腺后,我们将线性回归施加到乳腺导管的部件,并通过与浓度点的平均最小距离的度量估计浓度程度。 DDSM乳房X光学术图像上的实验结果表明,这些方法可能有助于成功地检测这些特征。

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